Association between Parkinson disease and selenium levels in the body: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Parkinson disease (PD) is a common neurodegenerative disorder, but its pathogenesis is still not entirely understood. While some trace elements, such as selenium, iron, and copper, are considered pivotal in PD onset due to their role in oxidative stress, the association between selenium concentrations and PD susceptibility remains ambiguous. METHODS: A systematic review and meta-analysis was conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and framed by the Patient, Intervention, Comparison, Outcome paradigm. Data were sourced from 4 prominent electronic databases: PubMed, Embase, Web of Science, and Cochrane Library. Eligible studies must have had a PD case group and a control group, both of which presented data on selenium concentrations. The quality of the studies was assessed using the Newcastle-Ottawa Scale. RESULTS: Of 1541 initially identified articles, 12 studies comprising a total of 597 PD cases and 733 controls were selected for the meta-analysis. Pronounced heterogeneity was observed among these studies. When assessing blood selenium levels, no significant difference was found between patients with PD and the controls. However, when examining the cerebrospinal fluid, selenium levels in PD patients were significantly elevated compared to controls (standard mean difference = 1.21, 95% CI 0.04-2.39, P < .05). Subgroup analyses, sensitivity analyses, and evaluation of publication bias were performed to ensure data robustness. CONCLUSIONS: Elevated selenium levels in cerebrospinal fluid may be associated with a higher risk of Parkinson. Further prospective research is required to solidify this potential link and to offer avenues for novel therapeutic interventions or preventive measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".